📖 ~1 min read
Table of contents
Symptom & Impact
Load average remains elevated and user transactions degrade during peak periods.
Environment & Reproduction
RHEL 7 app server where batch jobs and online traffic contend for memory and disk.
Root Cause Analysis
Combined memory pressure and slow storage produce high iowait and scheduler queue buildup.
Quick Triage
Check top, iostat -x, vmstat, and sar to identify dominant bottleneck dimension.
Step-by-Step Diagnosis
Trace top processes, inspect journalctl for kernel reclaim events, and confirm storage latency trend.

Solution – Primary Fix
Throttle batch concurrency, optimize memory usage, and relocate heavy I/O paths to faster storage.
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Solution – Alternative Approaches
Apply cgroups/resource controls and tune I/O scheduler parameters per device profile.
Verification & Acceptance Criteria
Load average aligns with CPU core count and p95 response time returns within SLO.
Rollback Plan
Undo recent tuning settings and restore previous scheduler/cgroup config if regressions appear.
Prevention & Hardening
Separate batch and latency-sensitive workloads and maintain capacity guardrails.
Related Errors & Cross-Refs
High iowait, blocked process alerts, periodic application timeouts during batch windows.
Related tutorial: View the step-by-step tutorial for rhel-7.
View all rhel-7 tutorials on the Tutorials Hub →
Browse all common problems & solutions on the Tutorials Hub.
References & Further Reading
RHEL tuning profiles, sar/iostat analysis guides, workload isolation best practices.
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